Abstract 3419: Demographic, health history, and lifestyle factors in association with biomarkers of colorectal cancer prognosis: A pilot study
Bibliographic record
Abstract
Abstract Background/Objectives: Multiple demographic, health history, and lifestyle factors have been associated with prognosis of colorectal cancer (CRC), but the mechanisms underlying these associations remain poorly understood. Knowledge of these mechanisms could reveal new strategies to improve outcomes among CRC patients. The primary objective of this project was to explore the association of these factors, which were assessed pre-diagnostically, with expression of two biomarkers in CRC tumors, SPARC and PD-L1, for which lower and higher levels of expression, respectively, have been previously associated with poorer CRC prognosis. Methods: Participants were drawn from the British Columbia Generations Project (BCGP). At the time of recruitment, they completed a detailed questionnaire that ascertained demographic factors (e.g., biological sex and household income), health history (e.g., personal history of CRC screening), and lifestyle factors (daily fruit and vegetable consumption and alcohol consumption). Formalin-fixed paraffin-embedded blocks (FFPE) with adequate volumes of tumor were obtained for 49 incident CRC cases diagnosed within the BCGP. Cores were extracted from the blocks to create tumor tissue microarrays (TMAs). Slides created from thin sections of the TMAs were stained with SPARC and PD-L1 antibodies and then imaged and analyzed to calculate H-scores as measures of expression in both epithelial and non-epithelial tissues. Linear regression analyses were conducted to evaluate associations between the various factors and ln-transformed H-scores. Results: Compared to non-smokers, smokers, on average, had 47% lower SPARC H-scores (p=0.05) in the epithelial tissues of their CRC tumors. Individuals with incomes higher than $74,999/year had 33% higher SPARC H-scores (p=0.04) in their CRC tumor non-epithelial tissues than those who earned less than $74 999/year. Females had 2.8-fold greater PD-L1 H-scores (p=0.005) in their CRC tumor epithelial tissues than males. Compared to those without a history of CRC screening, those with a history of CRC screening had 2.2 and 2.0-fold greater PD-L1 H-scores in their epithelial and non-epithelial CRC tumor tissues, respectively. Conclusion: Larger-scale studies with prognostic data are needed to confirm our findings, but our results suggest that differences in the expression of SPARC and PDL-1 may contribute to the previously observed impacts of some demographic, healthy history, and lifestyle factors on CRC prognosis. Citation Format: Umaimah Zanif, Isabella Tai, Stephen Yip, Sindy Babinszky, Katy Milne, Peter Watson, Rachel Murphy, Parveen Bhatti. Demographic, health history, and lifestyle factors in association with biomarkers of colorectal cancer prognosis: A pilot study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3419.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".